Rate-Distortion for Reversible Causal Nets under Closure-Preserving Fidelity (opens in new tab)

We develop a semantic rate-distortion theory for reversible logging under a closure-preserving fidelity criterion. An execution history is modeled as a finite set of logged facts, and rollback-relevant meaning is captured by a monotone semantic closure induced by an effective rule system such as Datalog. We introduce a bounded distortion that edits one logged fact and measures the resulting change in closure. A canonical deletion scan decomposes...